System and method for managing healthcare costs

ABSTRACT

Disclosed is a system and method for creating a financial index related to healthcare costs. A financial derivative instrument can be created from the index. Using the financial derivative instrument, an entity can hedge against unexpected fluctuations of healthcare costs.

FIELD OF THE INVENTION

The present invention generally relates to the fields of healthcare andfinance. Specifically, the present invention relates to a system andmethod of managing the risks associated with unreliable healthcarecosts.

BACKGROUND OF THE INVENTION

Individuals, enterprises, and corporations are continually exposed tothe risk of future events beyond their control, which can eitherpositively or negatively impact their financial stability. Acorporation's financial stability is expressed in terms of yearlyprofit, the primary financial metric for many of its publicly availableperformance indicators. These indicators, including earnings per share,net income, and income growth are important to the success of acorporation because investors look to these indicators to assess whetherto invest in the corporation. If the indicators are positive andindicate growth, investors are more likely to invest in the corporation.Therefore, it is important for a corporation to limit events that couldnegatively impact these indicators.

Risk can take many forms in view of the variety of future events thatmay occur. For example, some types of risk concern technicalphenomena—the breakdown of a power plant, aircraft engine failure, orthe damage to, or failure of, orbiting telecommunications satellites.

Another type of risk is economic in nature. Examples include fluctuationof commodity prices, currency exchange rates, interest rates, propertyprices, share prices, inflation rates, and market event based indices.Economic risk, also known as price risk, is the primary concern offinancial markets.

Financial markets measure risk in terms of volatility, which is commonlydefined as a statistical measure of the tendency of a market, security,or derivative to rise or fall sharply within a given period of time. Ifthe tendency is for a security to rise or fall very sharply, thesecurity is said to be highly volatile.

Volatility is an important component in the valuation of many financialderivatives. For example, when determining the value of an option,volatility is used as an independent variable that denotes the extentwhich the return of the underlying asset (e.g., stock prices) willfluctuate between the initial date of the option and its expirationdate. In this way, volatility is an essential element when determiningthe level of option prices. If volatility is high, the premium (i.e.,cost to purchase) on the option will be relatively high, and vice versa.Once you have a reliable measure of statistical volatility for anyunderlying asset, the fair market value of an option is calculable byutilizing a standard options pricing model.

However, the task of determining the volatility of a given financialinstrument is not straightforward. As a result, many methods have beendeveloped, and these methods vary greatly in their design, assumptionsand results. Often management of various risks is performed using arcanetechnical language that varies from one functional area to another.

Normally a corporation delegates the responsibility of risk managementto a risk manager, who considers the issues of probability and severityseparately. Accordingly, sufficient data to accurately determine avolatility function is rarely available making it extremely difficultfor organizations to place consistent valuations on associated risks,and to subsequently determine how to most accurately optimize theallocation of resources across an entire enterprise.

As a result, resources are allocated based upon either historicalhappenstance (i.e. the organization is aware of a recent large loss thatincreases its sensitivity to the risk associated with a particularhazard) or the organizational ability of the manager (i.e. the managergathers more resources within the organization).

Some risk managers utilize more subjective ranking systems to order therelative severity, probability and control costs. Labels may beassociated to each outcome indicating a subjective valuation of theseverity and probability. For example severity may be ranked with labelssuch as “high,” “medium,” or “low.” Probability may be ranked withlabels such as “certain,” “likely”, “unlikely,” or “rarely.” The cost tocontrol the risk can similarly be ranked as “high”, “moderate” or “low”.Certain ranking methodologies purport to apply equally to all risks inan organization, but do not establish consistent operational definitionsand measurement methodologies across the various functional areas.“High” and “likely” labels indicate different levels of risk todifferent individuals. Existing methodologies do not recognize theinterdependencies that exist between various risk controls, nor do theyanswer the question of whether economic value is being created by riskcontrol efforts. In addition, quantifying risk in a subjective mannercan lead to widely disparate results. Consequently, subjective rankingis often used as a screening method to determine relevant data sources.

After identifying likely volatile sources, risk managers generallyattempt to mitigate the adverse consequences associated with thatvolatility. A traditional, well known mitigation method is thepurchasing of insurance. Insurance is the simple transfer of risk fromone party, the insuree, to another party, the insurer in exchange forthe payment of a fixed premium price. Purchasing insurance to mitigatehas several advantages. First, large entities with considerableexperience with insuring a particular type of risk can often accuratelypredict the probability of loss, which enables insurers to set fairlyaccurate pricing. Second, insurers are able to pool risks by creating alarge, diversified portfolio of policies. That is, by issuing a largenumber of insurance policies, an insurer can diversify its risk andreduce premiums to the consumer.

However, there are several disadvantages to using insurance as a riskmanagement tool. While an insurer may accurately predict the probabilityand amount of loss, the administrative expenses associated withmaintaining the accuracy of these functions are high. Also, insurancecompanies must deal with adverse selection because an insurer oftencannot differentiate between a risk that never occurs and an eventinsured against which actually happens. Finally, insurers must deal withthe “moral hazard.” That is, once a risk has been insured, the insurermust be concerned that the insuree may exercise less careful to protectagainst the risk that may occur.

To compensate for the disadvantages, insurers must transfer some of theadditional risk to the insuree by raising premium costs. As a result,the cost to protect against a given risk is often higher than it wouldbe without the need to protect the insurer's additional risk. Of course,if the costs associated with managing risk by purchasing insuranceoutweigh the protections provided by the insurance, risk managers wouldbe loath to purchase it. As a result, insurance is inherently animperfect risk management system.

An alternative risk management tool is a process known as hedging,wherein parties exchange derivative instruments in order to offset theprice risk associated with fluctuations in cash markets.

Many entities including commercial firms, consumers, and producersutilize a hedging technique to protect themselves from price risk.Hedging enables a party to transfer risk to another party because theparties leverage related products and services which respond similarlyto the same economic factors. This leverage of related products and/orservices is known as correlation.

An entity can use any of several derivatives in the hedging process. Thesimplest of such derivatives is known as a forward contract, which is atransaction wherein a buyer and a seller agree upon price and quantityfor delivery of a specific service or commodity at a future point intime. While such a forward contract transfers risk, there aredisadvantages to utilizing it as a risk management tool. For example,forward contracts are not standardized, so each transaction must benegotiated individually. In addition, while such forward contracts arelegally binding, upon default a party must resort to the legal systemfor recovery. As a result of theses disadvantages, transaction costsassociated with negotiating, maintaining and enforcing forward contractsare often unnecessarily high. Therefore, forward contracts are generallyinefficient risk management tools.

Of course, in an attempt to compensate for the inefficiencies associatedwith variable-term forward contracts, they can be standardized as toinclude specific terms. Standardized forward contracts are known asfutures contracts and are generally standardized with respect toquantity, time, and place for delivery of goods and services. Becausefutures contracts are standardized, an entity can theoretically purchaseand sell futures contracts without ever actually taking physicaldelivery of the subject of the contract.

To eliminate the need for legal enforcement of a forward contract, amargin system was created to prevent buyers and sellers from defaultingon their contract. In a margin system, the buyer and the seller of afutures contract deposit cash to a margin account maintained by a thirdparty, usually an exchange or a bank, as collateral to guaranteeperformance of the futures contract. In addition, a margin may be“marked-to-market,” whereby the amount of money deposited into a marginaccount is updated continuously as the price of the underlyingderivative fluctuates.

Since the terms of a futures contract are standardized and delivery neednot ever be completed, a properly executed contract is all that isrequired for buying, selling, and trading the contract, making theprocess fairly liquid. To improve the liquidity of this process,exchanges were formed to facilitate these transactions on a largerscale. Currently, exchanges are the preferred forum for trading futurescontracts because risk managers appreciate the benefits of standardizedfeatures.

Futures options are analogous to futures contracts. The differencebetween the two is the fact that with futures options a party is notactually obliged to actually accept delivery of the underlyingcommodity. Instead, a party has the right to refuse delivery. The resultis that unlike futures contracts, futures options are not subject tomargin calls (i.e., the instrument is not marked to market unless aparty actually takes delivery) and have lower potential risk. There aredisadvantages to purchasing a futures option. For example, because oneparty has the right to refuse delivery of the futures option, thefutures option is more expensive to purchase that a futures contract.The higher price negatively impacts the return of the instrument,resulting in a lower yield. Because the yield is lower, it is a moreinefficient risk management tool than a standardized futures contract.

Typical buyers and sellers of derivative instruments have a vestedinterest in the fluctuation of price rates and attempt to manage theirrisk accordingly. Alternatively, certain buyers or sellers (e.g., aspeculator) can purchase the instrument without having a vested interestin the fluctuation of prices. A speculator will purchase or sell afutures instrument when he or she believes feels that he or she canpredict what will happen with a particular price risk more accuratelythan the market.

Speculators are generally parties who purchase a derivative such thatthey will experience financial gain when the price fluctuation of thederivative is actually higher than an expected threshold, or sell aderivative such that they will experience financial gain when the pricefluctuation of the derivative is lower than expected.

For example, consider a wheat farmer who wishes to sell his upcomingharvest. While prices for his crop remain steady, the farmer is worriedthat the value of his crops at harvest time will drop. The farmer(seller) can agree to deliver his wheat at harvest time to a miller,(buyer), who is worried that the price of wheat will increase betweenthe contract date and the harvest (delivery) date. The farmer and themiller have both attempted to manage the risk of the commodity, namelywheat. Note that if the price of wheat rises, the miller is said to gainvalue because the contract was executed at a lower price. Conversely, ifthe price of wheat falls, the farmer gains value because the contractwas executed at a premium over the price the farmer could have obtained.

The same principles hold for intangible financial products and services.For example, consider an entity that holds a contract to sell a productin a foreign market that will be paid for in foreign currency. If theforeign currency increases in value relative to the domestic currency,it will convert into less domestic currency. To protect itself againstthis currency risk, the domestic entity can buy a foreign currencyfutures contract. Similar to the farmer/miller example, if the foreigncurrency appreciates, the loss on conversion on the initial contract isoffset by the increased value of the futures contract. As a result,hedging is the preferred method of managing risk regarding price risksassociated with currency fluctuation.

Although there are numerous benefits to hedging, risk managers do notcurrently hedge against every contingency. To determine if a riskmanagement strategy is needed, risk managers generally utilize a simplecost-benefit analysis. If the risk that needs to be hedged has only asmall impact on an entity's business it may decide that hedging againstthat risk is unnecessary. Similarly, if the exposure is minimal, riskmanagers may be unwilling to invest limited resources to hedge. As aresult, a company typically only hedges large expenditures and/orcommodities that substantially impact the bottom line due to theirunderlying volatility.

For example, consider an entity that has a large exposure to inflation.To manage this risk the entity can purchase and/or trade a ConsumerPrice Index (CPI) future. The CPI index is a measure of inflation basedon publicly available information. Since almost every entity is exposedto inflation related price risk there is a large market for buyers andsellers who wish to manage this risk and the CPI index market trades ata high volume. While it can be generally utilized effectively to hedgeshort-term changes in inflation, and the index price is stable becauseit is based on government-published historic data, because it is a newtype of futures contract the total number of contracts available islimited. In addition, the CPI index is not an accurate measure of thevolatility of uncorrelated products and services (e.g., healthcare)because uncorrelated products and services increase in price at adifferent rate than inflation.

By way of example, healthcare costs in the United States are presentlyincreasing at two to three times the rate of inflation and at four timesthe rate of wage increases. In an attempt to measure the increase inhealthcare costs, entities rely on the healthcare trend, which indicatesthe percentage increase of healthcare expenditures per capita over apredetermined period of time. The components of the healthcare trend arehighly variable, making the healthcare trend extremely volatile. Forinstance, general inflation, consumer demand, government regulation,drug costs, unit cost, seasonality, and annual fluctuations in severityof variable illness, all of which are exemplary components of thehealthcare trend, are very volatile. Therefore entities that attempt tomanage health related expenditures have difficulty budgeting andforecasting these costs due to this volatility, which affects theentity's bottom line. Because of the direct impact of sharply risinghealthcare costs on an entity's financial stability, managing the pricerisk of healthcare related costs is vital.

For example, a Fortune 100 company like General Motors has highfinancial exposure to such risk factors as currency risk, credit riskfrom its financing division, interest rate risk from its financingdivision, and fuel cost risk from the sale of automobiles. Thesefinancial risks are correlated to significant sources of revenue from(or significant expenditures related to), automobile products andservices. General Motors therefore hedges against these risks in oneform or another utilizing financial derivative instruments.

In 2003, General Motors (GM) spent $4.8 billion on healthcare for itsemployees, which constituted an expenditure greater that its expenditurefor steel. Because healthcare costs comprise a large percentage ofGeneral Motor's expenditures, one would expect it to manage itshealthcare risk by utilizing financial derivatives. However, becausethere is no reliable method for managing its healthcare risk in thismanner, General Motors does not manage healthcare risk using financialderivatives. Instead, it relies on other risk management techniques.

Presently, the only viable method of managing the risk associated withhealthcare costs is for an entity to purchase health insurance. Theinsurance premiums associated with such insurance have been rising at analarming rate due to increasing costs that reflect the inherentvariability of the healthcare industry, such as the cost of prescriptiondrugs. As a result, the present system for managing risk associated withhealthcare costs (i.e., health insurance) is inefficient.

As premium costs continue to rise, insurance companies presently offer avariety of insurance types in an attempt to manage price risk andvolatility of healthcare expenditures.

One type of the insurance now offered is a method of reducing healthcarecosts known as stop-loss insurance.

Stop-loss insurance is purchased by self insured employers in an attemptto stabilize their healthcare costs. While a typical self insuredemployer can predict the approximate number of doctor visits itsemployees will have in a given year, it cannot predict the number of“catastrophic events” (e.g., premature births, cancer, and organtransplants)that will occur in a given year. The costs associated withthese procedures can be devastatingly high to a self insurer so thereexists a need to hedge against this type of risk.

There are two main types of stop-loss insurance. The first is known asIndividual Stop Loss “ISL,” sometimes called Specific Stop Loss.Individual Stop Loss protects an employer against expenditures by singleindividuals which exceed a predetermined dollar limit chosen by theemployer. For example, if an employee of the insured incurs injuries inan accident that requires expenditures that far exceed the premium'sstated deductible, the ISL insurance would reimburse the employer forall associated expenses beyond a predetermined dollar amount.

The second type of stop-loss insurance is known as Aggregate Stop Loss(ASL), or Excess Risk Insurance. Aggregate Stop loss insures an employeragainst the total expenditures by its employees as compared to apredetermined dollar amount. An employer typically purchases ASL tocover against 125% of the level of expected claims predicted by theinsurance carrier. For example, a mid sized self insurer with $4 millionin expected claims could purchase a stop loss policy that initiates when$5 million in claims are incurred.

Despite the obvious advantages associated with the various types of stoploss insurance, there are numerous disadvantages. For example,conservative pricing and limited availability of stop loss insurancepolicies severely curtails the usefulness of stop loss insurance tosmall health plans with limited financial resources. In contrast, largecompanies can afford the costs associated with a few catastrophicclaims, so the steep cost of stop loss insurance becomes economicallywasteful. Consequently, stop loss insurance is limited to mid-sized selfinsured employers because such entities often do not have large enoughcash reserves or generate enough income to cover the costs associatedwith several catastrophic claims. In addition, stop loss insurancesolutions maintain extreme volatility because typical stop loss plans donot take effect until the incurred claims exceed a 25% threshold.

Because current healthcare risk management techniques have limitedsuccess and sharply rising healthcare costs continue to impact anentity's financial stability, there is a clear need in the art for asystem and method to more effectively manage the risk associated withhealthcare costs. The present invention overcomes the variousdeficiencies associated with traditional healthcare risk managementtechniques by creating a novel healthcare index and associated financialderivative instrument that allows risk managers to effectively andefficiently hedge the highly volatile fluctuations associated withpredicting healthcare costs.

SUMMARY OF THE INVENTION

Disclosed is a method for creating a healthcare related index. Ingeneral, the method entails gathering a source of data, assessing it forrelevance to the overall healthcare trend, (or a particular subsetthereof), and calculating an index value based on the most relevantsource of data. Any source of data can be used, but it should closelycorrelate to the United States healthcare trend. For example, thefollowing data sources are known to have at least some correlation withthe United States healthcare trend: the medical CPI, the producer priceindex, national health accounts, medical expenditure panel survey,Medicare economic and price index, Kaiser/HRET annual employer healthbenefits survey, AHA annual survey, Mercer national survey of employersponsored health plans, Ingenix, Milliman health cost index, andMedstat. Of course, any data source that correlates with the healthcaretrend can be used in accordance with the present invention withoutdeparting from the spirit of the invention.

The data source can be assessed for relevance to the overall healthcaretrend (or a particular subset thereof) in any well known statisticalmanner. For example, the data source can be visually inspected forrelevance via a graph, spreadsheet, or any other similar manner. Inaddition, a variety of well known statistical software programs andtechniques can be utilized to determine whether the data source isrelevant.

Finally, the data source is used to create a healthcare relatedfinancial index. Any well known mathematical approach can be used tocreate the index. For example, the relative values of the data can beadded together to form an aggregate index value. Alternatively, the datacan be assigned different statistical weights to create a weightedaverage or the data can be normalized on a per capita basis. Indeed, anywell known mathematical approach can be used to create an index value,as long as the index value accurately reflects the United Stateshealthcare trend.

Also disclosed is the creation of a healthcare derivative instrument foruse in the management of healthcare related expenditures. Once such aderivative exists, it will attract a large market for buyers and sellersof the derivative as a method of managing risk. For example, typicalbuyers would generally comprise entities which currently providedhealthcare insurance related services and could be self insuredemployers, entities with large or mid-sized health plans, re-insurers,the United States and/or foreign governments, and speculators. Typicalsellers would generally comprise entities which provide healthcareservices and could include hospital systems, pharmaceutical companies,medical supply companies, healthcare sector mutual fund companies,physician groups, re-insurers, and speculators. Of course, other partiescould purchase healthcare related derivatives as well.

A healthcare derivative instrument is constructed such that pricefluctuation of the instrument correlates to the price fluctuation ofhealthcare costs. This can be achieved by constructing an underlyingindex that responds primarily to fluctuating healthcare costs.

The healthcare index allows healthcare related derivative products to betraded on a publicly available exchange, such as the Chicago BoardOptions Exchange. Benefits associated with trading the financialderivative of the present invention an exchange include improvedliquidity and increased volume.

Finally, to increase trading of a derivative instrument, the derivativemust be credible. It must therefore be based on accurate, objective,publicly available data. Therefore, an essential component of ahealthcare related financial derivative in accordance with the presentinvention is a properly created healthcare index.

There are numerous potential sources of publicly available, objective,credible data in the field of healthcare. Examples include thegovernment, charitable foundations, trade organizations, professionalorganizations, and proprietary healthcare data companies.

The following table summarizes a small number of currently availabledata sources: TABLE 1 DATA SOURCES Frequency of Name Description of DataSource of Data Updates Data a Strong Indicator of: Medical CPI Measuresaverage change in medical care Bureau of Labor Monthly Hospital(Inpatient versus Outpatient) prices paid by urban consumers. Statistics(BLS) Professional Services Prescription Drugs and Medical SuppliesNursing Homes Producer Price Measures average change in prices chargedBureau of Labor Monthly Hospitals (1995) Index by suppliers of medicalcare. Statistics (BLS Physicians (1998) Pharmaceuticals Nursing Homes(2004) Medical & Diagnostic Lab (2004) Home Health Care (1997) NationalHealth Measures health care spending in the US by Centers for AnnuallyHospital Care Accounts type of service and source of payment. Medicareand Professional Services Medicaid Services Prescriptions Drugs, DME(CMS) Nursing Home & Home Health Investments Medical Nationallyrepresentative survey that Agency for Annually Hospitals (Inpatient &Outpatient) Expenditure Panel collects data on health status, access tocare, Healthcare Physician Services Survey health care use and expenses,and health Research and Prescription Drug insurance coverage of US.Quality Home Health Services Medicare Economic Measures changes in costof physicians' Centers for Quarterly Hospitals and Price Index operatingexpenses versus input prices for Medicare and Physician ServicesMedicare. Medicaid Services/ Home Healthcare Global Insights SkilledNursing Facilities National Income Measures personal consumption andBureau of Quarterly Hospitals and Product expenditures component of thegross Economic Professional Services Accounts domestic product. AnalysisPrescription Drugs Kaiser/HRET Nationally representative survey ofpublic Kaiser Family Annually Hospitals Annual Employer and privateemployers that measures Foundation/ Physician Services Health Benefitsemployer sponsored health insurance Health Research Employer ExpensesSurvey coverage. and Educational Trust AHA Annual Survey ofapproximately 6,000 hospitals American Hospital Annually HospitalsSurvey that reports organization structure, staffing, AssociationPhysician Services utilization, and financial data. Mercer NationalSurvey of public and private employers that Mercer Human AnnuallyHospitals Survey of Employer reports data on premium & contributions,Resource Employer Expenses Sponsored Health and plans design. ConsultingPlans Ingenix Database of health expenditures on Ingenix VariesHospitals employees from self-funded employers. Physician ServicesEmployer Expenses Milliman Health Measures the average rate of increasein Milliman USA Quarterly Hospital (Inpatient & Outpatient) Cost Indexmedical costs for a typical $250 deductible Physician Servicescomprehensive major medical plan. Prescription Drugs Medstat Database ofhealth expenditures on various Medstat Varies Hospitals commercial,Medicare, and Medicaid plans. Physician Services

Also disclosed is a method of utilizing a healthcare derivative productto create various portfolios of holdings commonly known in the art as“baskets.”

The preferred embodiment of the present invention utilizes data derivedfrom the National Income & Product Accounts “NIPA” in the creation of ahealthcare index. At the present time, utilization of NIPA data resultsin the most accurate healthcare index in accordance with the presentinvention. However, as one of ordinary skill in the art would recognize,economic factors can vary greatly over a short period of time andtherefore any data source, whether currently existing or created in thefuture may be utilized to create a healthcare index. NIPA data iscomprised of discrete accounts related to specific healthcare productsand services, and therefore the index of the present inventioninherently contains discrete, easy to price, targeted segments, ortranches. As a result, an entity need not purchase a financialderivative based solely on the healthcare index. Rather it can determinespecific areas that have higher occurrences of volatility. For example,if an entity incurs healthcare costs in large part related to the costof providing prescription drugs, that entity can more effectively manageits healthcare risk by purchasing a healthcare derivative based solelyon the prescription drug tranche.

As another example, a prescription drug index can be created in themanner previously disclosed. Advantageously, NIPA data containspredetermined, discrete data that correlates to several healthcarefactors. This data can be used to create an index that correlates to theoverall healthcare trend or that correlates to any of the otherhealthcare factors (e.g., prescription drugs).

After creating the healthcare index based on a data source such as NIPA,the index is used to create an associated financial derivative. Thefinancial derivative can be any financial derivative known to one ofordinary skill in the art, such as a futures contract, a forwardcontract, or a futures option. The price of the healthcare derivative isrelated to the healthcare index because each derivative represents ashare of the healthcare index. By using a derivative with standardizedfeatures such as quantity and delivery date, the derivative can then betreated as a commodity on an exchange.

The present invention also discloses a method for using the associatedderivative instrument to hedge the risk associated with healthcarecosts. To accomplish this, an entity creates a hedge ratio to determinethe number of financial derivatives to purchase in order to mitigate adeviation in predicted healthcare related prices. After determining thehedge ratio, an entity can buy or sell the appropriate derivatives.

Accordingly, an object of the present invention is to provide a systemand method which enables an entity to hedge its risk associated withhealthcare expenditures.

Another object of the present invention is the creation of a healthcareindex that is correlated with the healthcare trend to facilitate thecreation of an associated financial derivative.

Another object of the present invention is to utilize publicly availabledata to create a healthcare index.

Still another object of the present invention is the creation of afinancial derivative having a price determined by an accurate healthcareindex.

Yet another object of the present invention is to utilize the healthcareindex to create a standardized healthcare related financial derivativeinstrument.

Another object of the present invention is to create a market toexchange a standardized healthcare related financial instrument.

It is another object of the present invention to create a healthcareindex related instrument that is available for purchase over thecounter.

Still a further object of the present invention is to use tranched datato create healthcare index sub-indices.

Yet a further object of the invention is the creation of an algorithmthat allows entities to objectively measure healthcare risk.

BRIEF DESCRIPTION OF THE DRAWINGS

A further understanding of the present invention can be obtained byreference to a preferred embodiment set forth in the illustrations ofthe accompanying drawings. Although the illustrated embodiment is merelyexemplary of systems for carrying out the present invention, both theorganization and method of operation of the invention, in general,together with further objectives and advantages thereof, may be moreeasily understood by reference to the drawings and the followingdescription. The drawings are not intended to limit the scope of thisinvention, which is set forth with particularity in the claims asappended or as subsequently amended, but merely to clarify and exemplifythe invention.

FIG. 1 is a flow chart generally depicting the method of creating afinancial derivative index.

FIG. 2 is a depiction of graphically comparing potential source data topotential buyers and sellers.

FIG. 3 is a tabular depiction of the component parts of a preferred datasource.

FIG. 4 is a graphical depiction of the differences between severalconstituent components of a preferred data source.

FIG. 5 is a flow chart depicting a method in which a large company canhedge against healthcare volatility.

FIG. 6 is a flow chart depicting a method in which a health careprovider can hedge against healthcare volatility by initially sellingfutures contracts with an underlying price determined by a healthcareindex and later settling its futures contracts.

FIG. 7 is a graphical depiction of the creation of sub-indices from ageneral Healthcare Index.

FIG. 8 is a flow chart depicting a method in which a hospital can hedgeagainst healthcare volatility by initially purchasing futures contractswith an underlying price determined by a healthcare index and latersettling its futures contracts.

FIG. 9 is a flow chart depicting a method in which a Company can hedgeagainst healthcare volatility by initially purchasing a basket ofderivative contracts and later settling its derivative contracts.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

A detailed illustrative embodiment of the present invention is disclosedherein. However, techniques, systems and operating structures inaccordance with the present invention may be embodied in a wide varietyof forms and modes, some of which may be quite different form those inthe disclosed embodiment. Consequently, the specific structural andfunctional details disclosed herein are merely representative, yet inthat regard, they are deemed to afford the best embodiment for purposesof disclosure and to provide a basis for the claims herein which definethe scope of the present invention.

Moreover, well known methods, procedures, and substances for bothcarrying out the objectives of the present invention and illustratingthe preferred embodiment are incorporated herein but have not beendescribed in detail as not to unnecessarily obscure aspects of thepresent invention.

None of the terms used herein, including “future”, “futures contract”,“derivative”, “instrument”, and “option” are meant to limit theapplication of the invention. The terms are used interchangeably forconvenience and are not intended to limit the scope of the invention.Similarly, the use of the term “company” or “corporation” is not meantto limit the scope of the invention to one type of entity, as any entityor individual can utilize the present invention. The following presentsa detailed description of a preferred embodiment of the presentinvention.

Referring to FIG. 1, depicted is a method of calculating the value of ahealthcare derivative index as shown in step 109. Initially, datarelated to healthcare can be gathered 101 from any source as depicted instep 101. In a preferred embodiment this data is made availableperiodically from a public source and has proven to be credible,reliable, and frequently disseminated. The data source according to thepreferred embodiment is National Income & Product Accounts data forreasons discussed below. An ordinary skilled artisan would recognizethat any data source could be utilized including: the medical CPI, theproducer price index, national health accounts, the medical expenditurepanel survey, the Medicare economic and price index, the Kaiser/HRETannual employer health benefits survey, the AHA annual survey, theMercer national survey of employer sponsored health plans, Medstat, theMilliman Health Cost Index, Ingenix, or any other data source currentlyknown or developed in the future. In the preferred embodiment of thepresent invention, the data is downloaded from an online source (e.g.,the internet) and stored in a database, but any well known method ofgathering data can be utilized to gather the data as depicted in step101 without departing from the spirit of the invention.

According to the present invention, after data is gathered 101, the datais assessed and filtered with respect to its relevance as depicted instep 103 by comparing the data to healthcare related economic factors.In the preferred embodiment of the present invention, the data isassessed according to a subjective ranking system, including any numberof factors, including but not limited to: relevance, timeliness,reliability, understandability, market applicability, accessibility, andindependence of the data. The value of each factor is subjectivelyassigned according to a three point scale (high, medium, or lowpriority) all of which are equally weighted. Any other method and meansfor assessing and categorizing the data can be used without departingfrom the scope of the invention. For example, alternative embodiments ofthe present invention can assign values to various features using a fivepoint (e.g., 5—highest, 1=lowest) scale. It is contemplated that anynumber of factors can be cited, and any subjective ranking system can beimplemented in accordance with the present invention.

The analysis of several presently available sources of data is depictedin Table 2. Of course, it is contemplated that a similar analysis can beconducted at any point in the future to consider contemporaneouslyavailable data sources. The results are tabulated below: TABLE 2COMPARISON OF DATA SOURCES Reliability/ Market/Industry Independence/Relevance Timeliness Consistency Understandability AcceptabilityAccessibility Neutrality Producer Price Index Medium High High High HighHigh High Kaiser/HRET Annual High Medium Medium High High High HighEmployer Health Benefits Survey Medical CPI Low High High High High HighHigh National Health Accounts High Low High Medium High High HighNational Income and Medium High High Low Medium High High ProductAccounts Medicare Economic and Medium Medium High Medium Medium HighHigh Price Index Mercer National Survey of High Medium Low High MediumMedium Medium Employer Sponsored Health Plans Ingenix High Medium MediumMedium Medium Low Medium Medstat High Medium Medium Medium Medium LowMedium Milliman Health Cost High Medium Medium Medium Medium Low MediumIndex Medical Expenditure Medium Low Low Low Medium High High PanelSurvey AHA Annual Survey Medium Low Medium Medium Medium Low Medium

To select the most compatible data pool for use in the system and methodof the present invention, the data sources that are deemed most useful(i.e., have the highest overall subjective rankings)are compared tohistorical buying and selling trends within the healthcare industry asdepicted in step 105. Comparisons can be made by plotting the dataversus a baseline indicative of the trends in the healthcare industryand visually inspecting the results to determine whether the dataadequately correlates. Alternatively, any statistical analysis can beimplemented as is known by one of ordinary skill in the art.

Referring now to FIG. 2, shown is an example of the comparison ofselected source data to historical buying trends in accordance with thepreferred embodiment of the present invention. Historical sell sidebaseline data 201 and buy side baseline data 203 are plotted as afunction of percentage change over time (in years). Generally, X axis205 represents the historical timeline, while Y-axis 207 represents thepercentage change of each of sell side baseline 201, buy side baseline203, Kaiser/HRET Annual Survey of Employer Health Benefits data 209 (apotential data source), and NIPA data 211 (a second potential datasource). Sell side baseline data 201 is derived from the National HealthAccounts and reflects the average change in health related services ofinvestors likely to sell healthcare related derivatives for riskmanagement purposes. Buy side baseline data 203 is derived from an equalweighting of both 1) the National Health Accounts and 2) the Kaiser/HRETAnnual Employer Health Benefits Survey and reflects the average changein health related services of investors likely to purchase healthcarerelated derivatives to manage risk. Any other source that reflectscontemporary potential buying and selling preferences can be utilized asbaseline values as well. After plotting baseline data 201 and 203,potential index data 209 and 211 are plotted on the same graph. In theexample depicted in FIG. 2, one potential data source is derived fromthe Kaiser/HRET Annual Employer Health Benefits Survey data 209 and asecond potential data source is based on the National Income and ProductAccounts “NIPA” data 211. Of course, any potential data source(including those listed in Table 2) can be plotted on the graph todetermine this relative correlation to baseline data for a given timeperiod to assess the relative viability of each data source. By usingthe graph a visual comparison can be made. In the example, a visualcomparison of NIPA data 211 reveals that it correlates well with sellside baseline 201. In addition, NIPA data 211 falls within the spread(i.e., the gap between the sell side baseline and the buy sidebaseline). This is advantageous because various parties (e.g.,speculators, buyers, and sellers) can utilize the index to manage therisks associated with healthcare costs. In contrast, Kaiser/HRET data209 does not visually appear to correlate with either the sell sidebaseline 201, the buy side baseline 203, or fall within the spread ofthe two baselines. This indicates that at the present time, Kaiser/HRETdata 209 data is not as advantageous as NIPA data 211.

Referring now to FIG. 1, after comparing data sources to potentialbuyers and sellers in step 105, a data source is chosen as depicted instep 107. In accordance with the present invention it is preferable toselect a data source that correlates with the preferences of buyers andsellers as depicted in FIG. 2. In the preferred embodiment, the datasource chosen in step 107 is the National Income & Product Accounts(NIPA) 211.

Once a data source is chosen as depicted in step 107, an index value iscalculated and generated as depicted in step 109. The index can becalculated using any well-known statistical measure, including but notlimited to linear regression and best-fit analyses. In the preferredembodiment, the index value is calculated from NIPA data and the indexvalue is created by adding the relevant data values (e.g., ophthalmicproducts and orthopedic appliances, medical care, and hospitals andnursing homes) while eliminating less relevant sub-components (e.g., newhome construction). The numerical value of this data is then normalizedbased on population trends as reported by any number of populationestimating agencies, including but not limited the United States CensusBureau and the Bureau of Economic Affairs. It is contemplated that anyother well known method of normalizing data or calculating an indexvalue can be used in accordance with the present invention.

FIG. 3 depicts the various components of the preferred data sourceaccording to step 107, NIPA data source 211. More specifically, FIG. 3depicts NIPA data relating to ophthalmic products and orthopedicappliances 211A, drug preparations and sundries 211B, and medical care211C. In the preferred embodiment of the present invention, thesecomponents of NIPA data source 211 are utilized to create a healthcareindex.

One of ordinary skill in the art will understand that it is contemplatedthat other means of combining component parts of NIPA data source 211 orcombining component parts of other data sources can be implemented inaccordance with the present invention. For example, in an alternativeembodiment of the present invention, NIPA data source 211 is composed ofa weighted average of various component parts 211A, 211B, and 211C. Inthis alternative embodiment, a healthcare index more sharply focused onvarious components can be created. In this way, a unique healthcareindex can be created for each sub-industry within the healthcareindustry utilizing the system and method of the present invention.

For example, FIG. 4 shows a graphical representation of certaincomponents of NIPA data source 211 as compared to the whole of NIPA datasource 211. More specifically, FIG. 4 depicts the percentage change ofthe value of each component, which is plotted on X-axis 407, over thecourse of time (by year) on Y-axis 409. In the alternative embodimentsdepicted in FIG. 4, potential data sources include component datarelated to Hospitals and Nursing Homes 401, Prescription Drugs “HCI-Rx”403, Insurance “HCI-Insurance ” 405 and NIPA data 211. FIG. 4illustrates the differences in volatility of the component parts of thehealthcare index created using NIPA data source 211.

In the alternative embodiment depicted in FIG. 4, selecting any of thedepicted component parts will enable creation of an alternative index inaccordance with the present invention. For the sake of clarity, anyindex created by utilizing one or more component parts of a data sourceshall be referred to as “sub-indices.”

Creating sub-indices is advantageous when the risk that the entitywishes to manage does not satisfactorily correlate to total NIPA datasource 211. It is also useful when an entity wishes to hedge a specific,localized risk.

For example, Prescription Drugs data 403 has not historically correlatedstatistically with NIPA data 211 even though prescription drugs data 403is a significant component of the data. If an entity wishes to hedge itsrisk associated with the volatility of prescription drug costs, aprescription drug sub-index can be created using prescription drug data403. That is, in accordance with the present invention, creation of asub-index calculating its value can be accomplished using any well-knownstatistical measure.

Once a data source is selected for creation of an index (e.g., asdepicted in step 107, FIG. 1) the associated index value can becalculated using any mathematical approach as previously disclosed. Forexample, referring to FIG. 3, a sub-index related to prescription drugscan be created using NIPA data 301. In addition, data 301 can benormalized in a well known manner. In a preferred embodiment, data 301is normalized on a United States population per capita basis.

In addition, it is contemplated that other sources of data can be usedto create sub-indices. For example, data related to worker'scompensation 303 and/or data related to medical care and hospitalization305 can be used in a similar manner to create additional sub-indices.That is, an index can be calculated to correspond to the overallworker's compensation trend.

FIG. 7 depicts examples of the creation of sub-indices from a generalhealthcare index. NIPA 211 serves as the source of healthcare index 711.Sub-indices were created in a manner consistent with the methoddescribed above to create prescription drug index 701 (derived fromprescription drug data 301) worker's compensation index 703 (derivedfrom worker's compensation data 303), and medical care andhospitalization index 705 (derived from medical care data 305). Ingeneral, the method used to calculate an index that correlates to theoverall healthcare trend (e.g., FIG. 1) is utilized to calculate indiceswhich correlate to specific subsets of the healthcare trend (e.g.,prescription drugs).

A preferred method of using the healthcare index of the presentinvention is to construct a financial derivative instrument thatutilizes the healthcare index as a price source. Types of financialderivatives include futures contracts and futures options, as well asother types well known in the art. In the preferred embodiment of thepresent invention, the derivative instrument utilized is a futurescontract comprised of a forward pricing contract with a settlement pricedetermined by the healthcare index and other standardized features.

More specifically, the derivate settlement price of the futures contractwill be determined in accordance with the annualized percentage changebetween the healthcare index on the settlement date and the index at thedate the derivative is purchased. The purchase date and settlement dateof the derivative coincide with the release of the healthcare index'sunderlying source data. (e.g., in the preferred embodiment, thederivative purchase date and settlement date will coincide with therelease of NIPA source data 211). Formulating a futures contract in sucha manner minimizes arbitrage opportunities and improves efficiency intrading markets because it ensures that every party receives theinformation at the same time. That is, it eliminates the problem ofasymmetric market information.

In the preferred embodiment of the present invention, the derivative iscreated having standardized features such that it can be offered on anexisting exchange. For example, a standardized futures contract istypically a forward pricing contract purchased on a margin that isassessed daily. In addition, they are marked to market and have standardsettlement dates.

Of course, there may be incremental margin requirements incurred withthe trading of this instrument. The exact amount initially depends onthe exchange, the type of futures contract, and the instrument'svolatility. In addition, for the purposes of the foregoing examples,brokerage fees are estimated to be approximately $10 per contract.

While offering the contract on an exchange does require purchasing it onmargin, most entities already have a margin account at the largerexchanges, so that this requirement will have little, if any impact oncash flow.

It is not necessary for the derivative instrument described in thepreferred embodiment of the present invention to be offered on anexchange. Rather, it is contemplated that alternative embodiments of thepresent invention can include unique derivative instruments offered“over the counter.” These alternatives allow for customization offinancial derivatives, including the creation of a basket ofderivatives.

The present invention further relates to a method of using a financialderivative to manage the risks associated with healthcare volatility.

Referring now to FIG. 5, shown is an example of a self insured employerusing a financial derivative based on a healthcare index to manage itsrisk against healthcare cost volatility in accordance with the presentinvention. Initially, an entity predicts its expected healthcare costsas depicted in step 501. Any means of predicting costs can be used, allof which are well known in the art. The process of the current inventionwill be demonstrated by an example in which a Company predicts a 10%increase in expected medical expenses, from $40 million to $44 millionusing any commonly known prediction technique. The Company also predictsthat in its worst-case scenario, the costs incurred will be $2 millionhigher than originally predicted. Conversely, the Company predicts itsbest-case scenario to be that its costs incurred are $2 million lessthan predicted.

After predicting its costs, the Company must determine the appropriatenumber of futures contracts to sell in order to effectively hedgeagainst the calculated risk associated with the prediction of step 501.To accomplish this, the Company calculates its hedge ratio 503 using theprice of contemporaneously available futures contracts based on thehealthcare index. In this example, it is assumed that contemporaneousfutures contracts are selling at $90, which reflects a 10% increase inthe NIPA healthcare index over the course of the year. Using this dataas a starting point, the Company decides how much risk exposure theywish to hedge against and how much of their cash holdings they willspend to hedge that exposure. These factors are combined to form a hedgeratio in any manner that is well known in the art. Indeed, today manyentities either calculate their own hedge ratios with respect tonon-healthcare risk or rely on consulting firms to help determine suchratios. Of course, other embodiments of the present invention allow forvarious other factors to be incorporated into a hedge ratio, as is wellknown in the art. The hedge ratio is then used in a well-known manner tocalculate the number of contracts to sell.

After determining the number of contracts to sell, the Company wouldsell the requisite number of contracts 505. In this example of theembodiment of the present invention, we assume that the Companydetermines that it will sell 40 contracts at $90.00 per contract. It isalso assumed that the value of the index on the date of sale is $4000.The Company can either construct custom futures contracts in the mannerpreviously described or use a standardized futures contract, and weassume the quantity of each standardized contract is 10,000.

The Company may then offer the futures contracts for sale privately,over the counter, or publicly on an exchange. In the presently describedembodiment, the contracts are offered on an exchange, but in alternativeembodiments, the contracts could be standardized and offered on anexchange or the Company could construct the contracts in any manner thatit chooses and offer them for sale in any manner.

After offering the contacts for sale, the Company can allow thecontracts to settle as shown in step 507. Alternatively, it can managethe futures contracts in any manner known, including repurchasing anyportion of the contracts it has offered on any day at a value determinedby the index price, or sell more contracts at the market price.

On the settlement date of the futures contracts, the Company deliversits contracts. The value of the healthcare index on the settlement dateis used to determine the settlement price. In the currently describedembodiment, it is assumed that on the settlement date the healthcarecost index increased to $4550. The contract value is then determined bythe below formula:100−(100*((Index Value on settlement date/index value on offer date)−1))Knowing that the value of the index at settlement is $4550 as the valueof the index at offering was $4000, the contract value of $86.25.

To determine its total profit or loss, the Company uses the formula:# Units/contract*# of contracts*price difference=Profit (Loss)In the previously described embodiment the Company would profit in theamount $1,500,000.

Note that when implementing the formula, the number of contracts isexpressed as a negative number to indicate that the Company sold them(i.e., if the Company had purchased the contracts, the value would bereflected as a positive number).

In the presently described embodiment, the healthcare index rose abovethe expected threshold of 10%. The actual percentage increase can bedetermined by using the below formula:((Index Value at Settlement/Index Value at Offering)/Index Value atoffering))*100%In the presently described embodiment, the index rose 13.75%. Becausethe volatility of healthcare costs was higher than expected and thehealthcare index is correlated to healthcare increases, the Company'syearly predictions were too low. It is assumed that the Company incurredmedical expenses of $46 million. To properly hedge against its erroneouspredictions, the Company applies the proceeds 509 from the sale of thecontracts (e.g. $1,500,000) to the increased cost of healthcare. In thepresently described embodiment, the Company has a net loss of $500,000,the difference between the increase in predicted healthcare costs andthe monies earned on the futures contract. While the Company incurred anet loss of $500,000, without hedging in accordance with the presentinvention, the Company would have incurred a net loss of $2,000,000.

Table 3 illustrates the benefits to the Company of hedging riskutilizing a financial derivative based on the healthcare index inaccordance with the present invention: TABLE 3 Risk ManagementComparison Base Case Company No Hedge Stop-Loss Futures 1. BudgetProjection Claims Incurred 2004 40.0 40.0 40.0 (in $millions) ExpectedTrend 2004-2005 10% 10% 10% Expected Claims 2005 44.0 44.0 44.0 NetExpected (Excluding 44.0 44.0 44.0 any reimbursement or cost from hedge)Low High Low High Low High Trend Trend Trend Trend Trend Trend 2. ActualExperience Actual Trend 2004-2005 5% 15% 5% 15% 5% 15% Actual Claims2005 42.0 46.0 42.0 46.0 42.0 46.0 (in $millions) Cost of Hedge N/A N/A1.0 1.0 N/A N/A Settlement of Hedge N/A N/A 0.0 (1.5) 1.5  (1.5) NetExpenses 42.0 46.0 43.0 45.5 43.5 44.5 3. Difference From Expected (2.0) 2.0  (1.0) 1.5  (.5) 0.5 (in $millions)

In calculating the content of Table 3, it is assumed that standard stoploss provisions apply,$250,000 premium cost for individual coverage witha premium of $900,000 and 125% aggregate coverage with a premium of$100,000. The result is a total premium of $1 million. In the currentlydisclosed embodiment, the premiums reflect a total reimbursement of $1.5million.

As the table illustrates, the Company's insurance costs were the leastvariable using a futures derivative in accordance with the presentinvention. If the Company chose not to hedge its risk, its totalvariability is ± $2 million wherein if its elects to utilize stop lossinsurance its exposure is limited to the premiums paid ($1 million) andits potential gain is limited to the maximum reimbursement ($1.5million).

However, by utilizing futures contracts based on a healthcare index tohedge against risks associated with healthcare costs, the company'stotal variability is limited to ±$500,000, which allows the Company tobetter predict its future earnings.

Referring now to FIG. 6, shown is an embodiment whereby a health careprovider can hedge against healthcare cost volatility by using futurescontracts based on a healthcare index in accordance with the presentinvention. The health care provider predicts its expected healthcarecosts as depicted in step 601, including total revenue (premiums of $1billion), incurred claim costs ($880 million), and administrativeexpenses ($80 million) for a predicted profit ($40 million). Thus, inthe presently depicted embodiment, the healthcare provider's worst-casescenario is that the costs incurred will be $40 million higher thanpredicted. Similarly, the healthcare provider's best-case scenario isthat its costs incurred will be $40 million less than predicted.

After predicting its costs, the healthcare provider must determine thenumber of futures contracts it needs to sell in order to effectivelyhedge by calculating its hedge ratio 603 using the price ofcontemporaneously available futures contracts based on the healthcareindex. In this example, it is assumed that contemporaneous futurescontracts are selling at $90.00, which reflects a 10% increase in theNIPA healthcare index over the course of the year. Using this data as astarting point, the healthcare provider decides how much risk exposureit wishes to hedge against and how much of its cash holdings it willspend to hedge that exposure. These factors are combined to form a hedgeratio in any manner that is well known in the art. Indeed, today manyentities either calculate their own hedge ratios with respect tonon-healthcare risk or rely on consulting firms to help determine suchratios. Of course, other embodiments of the present invention allow forvarious other factors to be incorporated into a hedge ratio, as is wellknown in the art. The hedge ratio is then used in a well-known manner tocalculate the number of contracts to sell.

After determining the number of contracts to sell, the healthcareprovider would sell the requisite number of contracts 605. In thisexample of the embodiment of the present invention, we assume that thehealthcare provider determines that it will sell 800 contracts at $90.00per contract. It is also assumed that the value of the index on the dateof sale is $4000. The healthcare provider can either construct customfutures contracts in the manner previously described or use astandardized futures contract, and we assume that the quantity of eachcontract is 10,000.

As in the previous example, the healthcare provider may offer thecontracts for sale privately, over the counter, or publicly on anexchange. Of course, the healthcare provider can construct the contractsin any manner that it chooses, and may offer them for sale in any mannerwithout departing from the spirit of the invention.

In this embodiment of the current invention, the margin is estimated tobe $4,000,000. As previously described, the margin amount is determinedby the particular exchange which is utilized for the transaction. Forthe purposes of this example, it is assumed that the contracts willtrade on the Chicago Mercantile Exchange in a manner similar to the CPIFutures Contract which has a margin requirement of $1,250 per quarter.Because for the purposes of this example it is assumed the healthcareindex related instrument is traded annually, an annual margin value of$5,000 per contract applies. Since 800 contracts are involved, theannual margin value for this transaction is calculated to be $4,000,000.

After offering the contacts for sale, the healthcare provider can allowthe contracts to settle as shown in step 607. Alternatively, it canmanage the futures contracts in any manner known, including repurchasingany portion of the contracts it has offered on any day at a valuedetermined by the index price, or sell more contracts at the marketprice.

On the settlement date of the futures contracts, the healthcare providerdelivers its contracts. The value of the healthcare index on thesettlement date is used to determine the settlement price. In thecurrently described embodiment, it is assumed that on the settlementdate the healthcare cost index increased to $4550. The contract value isthen determined by the below formula:100−(100*((Index Value on settlement date/index value on offer date)−1))Knowing that the value of the index at settlement is $4550 as the valueof the index at offering was $4000, the contract value of $86.25.

To determine its total profit or loss, the healthcare provider uses theformula:# Units/contract*# of contracts*price difference=Profit (Loss)In the previously described embodiment the healthcare provider wouldprofit in the amount $10,000,000. Note that when implementing theformula, the number of contracts is expressed as a negative number toindicate that the healthcare provider sold them (i.e., if the healthcareprovider had purchased the contracts, the value would be reflected as apositive number).

In the presently described embodiment, the healthcare index rose abovethe expected threshold of 10%. The actual percentage increase can bedetermined by using the below formula:((Index Value at Settlement/Index Value at Offering)/Index Value atoffering))*100%In the presently described embodiment, the index rose 13.75%. Becausethe volatility was higher than expected and the healthcare index iscorrelated to healthcare increases, the healthcare provider's yearlycost predictions were too low. To properly hedge against its erroneouspredictions, the healthcare provider applies the proceeds 609 from thesale of the contracts (e.g., $30 million) to the increased cost ofhealthcare. In the presently described embodiment, the healthcareprovider has a net loss of $10,000,000, the difference between theincrease in predicted healthcare costs and the monies earned on thefutures contract. While the healthcare provider incurred a net loss of$10 million, without hedging in accordance with the present invention,the healthcare provider would have incurred a net loss of $40 million.

Table 4 illustrates the benefits to the healthcare provider of hedgingrisk utilizing a financial derivative based on the healthcare index inaccordance with the present invention: TABLE 4 Hedging Comparison BaseCase Healthcare Provider No Hedge Futures Budget Projection 2005 InsuredPremium 1,000   1,000   (in $millions) Claims Incurred 2004 800 800Expected Trend 2004-2005  10%  10% Expected Claims 2005 880 880 AdminExpense 2005  80  80 Expected Total Costs 2005 960 960 Net ExpectedProfit  40  40 (Excluding any reimbursement or cost from hedge) Low HighLow High Actual Experience Trend Trend Trend Trend Actual Trend2004-2005   5%  15%   5%  15% Actual Claims 2005 840 920 840 920 (in$millions) Settlement of Hedge — —  30  (30) Actual Net Costs 9201,000   950 970 Actual Net Surplus  80  0  50  30 Difference FromExpected  (40)  40  (10)  10 (in $millions)

As the table illustrates, the healthcare provider has the leastvariability using a futures derivative in accordance with the presentinvention. If the healthcare provider chose not to hedge its risk, thetotal variability is ±$40 million. However, by utilizing a futurescontract based on a healthcare index to hedge against risks associatedwith healthcare costs, the healthcare provider's total variability islimited to ±$10,000,000. Using futures contracts represents the smallestvariability, which allows the healthcare provider to better predict itsfuture earnings.

Referring now to FIG. 8, shown is an embodiment of the present inventionwherein a hospital can manage the risks associated with healthcare costvolatility by purchasing futures contracts based on a healthcare index.As in the previous examples, the hospital first predicts its expectedhealthcare revenue as depicted in step 801. For the purposes of thisexample, assumptions include total revenue ($160.6 million) and totalexpenses ($125.6 million) for a predicted profit ($35 million). In theexample, the hospital's worst-case scenario is that the revenuegenerated will be $7.3 million lower than predicted. Similarly, thehospital's best-case scenario is that its revenues will be $7.3 millionmore than predicted.

After predicting its revenues, the hospital determines the number offutures contracts it needs to purchase in order to effectively hedge bycalculating its hedge ratio 803 using the price of contemporaneouslyavailable futures contracts based on the healthcare index. As in theprevious example, it is assumed that contemporaneous futures contractsare trading at $90.00, which reflects a 10% increase in the NIPAhealthcare index over the course of the year. Again, using this data asa starting point, the hospital decides how much risk exposure it wishesto hedge against by forming a hedge ratio in any manner that is wellknown in the art to calculate the number of futures contracts topurchase.

After determining the appropriate number of contracts to purchase, thehospital would purchase the requisite number of contracts 805. In thisexample of the embodiment of the present invention, we assume that thehospital determines that it will purchase 140 contracts at $90.00 percontract. It is also assumed that the value of the index on the date ofpurchase is $4000 and that the quantity of each contract is 10,000.

As in the previous example, the hospital may purchase the futurescontracts privately, over the counter, or publicly on an exchange.

In this embodiment of the present invention, the margin is estimated tobe $700,000. After purchasing the contacts the hospital can allow thecontracts to settle as shown in step 807 or it can manage the futurescontracts in any manner known or previously described.

On the settlement date of the futures contracts, the hospital acceptsits contracts. The value of the healthcare index on the settlement dateis used to determine the settlement price. In the currently describedembodiment, it is assumed that on the settlement date the healthcarecost index increased to $4250. The contract value is then determined bythe below formula:100−(100*((Index Value on settlement date/index value on offer date)−1))Knowing that the value of the index at settlement is $4250 as the valueof the index at offering was $4000, the contract value is $93.75.

To determine its total profit or loss, the hospital uses the formula:# Units/contract*# of contracts*price difference=Profit (Loss)In this case the hospital would gain $3.75 million. In this example, thehealthcare index did not rise above the expected threshold of 10%. Theactual percentage increase can be determined by using the below formula:((Index Value at Settlement/Index Value at Offering)/Index Value atoffering))*100%which yields 6.25%. Because the volatility was lower than expected andthe healthcare index is correlated to hospital stays, the hospital'syearly revenue predictions were too high. To properly hedge against itserroneous predictions, the hospital applies the proceeds 809 from thepurchase of the contracts (e.g., $3.75 million) to the decreasedrevenue. In the presently described embodiment, the hospital has a netloss of $3.25 million, the difference between the decrease in predictedrevenue ($7,000,000 million) and the monies earned on the futurescontract. While the hospital incurred a net loss of $3.25 million,without hedging in accordance with the present invention, the hospitalwould have incurred a net loss of $7 million.

Table 5 further illustrates the benefits to the hospital of hedging riskutilizing a financial derivative based on the healthcare index inaccordance with the present invention: TABLE 5 Hedging Comparison BaseCase Hospital No Hedge Futures Budget Projection # of Hospital Beds 600600 Average number of occupied 400 400 beds in 2004 Expected Trend2004-2005  10%  10% Expected average number 440 440 of occupied beds in2005 Expected Revenue 2005   160.6   160.6 Expected Total Costs 2005  125.6   125.6 Net Expected Surplus  35  35 (Excluding anyreimbursement or cost from hedge) Low High Low High Actual ExperienceTrend Trend Trend Tread Actual Trend 2004-2005   5%  15% 5%   15%  Actual average number of 420   460   420    460    occupied beds in 2005(in $millions) Settlement of Hedge — — 3.75 (3.75) Actual Net Revenue153.3 167.9 157.05  164.15  Actual Net Surplus  30.6  39.4 34.35  35.65 Difference From Expected  (4.4)  4.4 (0.65) 0.65 (in $millions)

As the table illustrates, the hospital has the least variability using afutures derivative in accordance with the present invention. If thehospital chose not to hedge its risk, the total variability is ±$4.4million. However, by utilizing a futures contract based on a healthcareindex to hedge against risks associated with healthcare costs, thehospital's total variability is limited to ±$650,000. Using futurescontracts represents the smallest variability, which allows the hospitalto better predict its future earnings.

As described generally above, the disclosed method of the presentinvention can utilize various sub-indices to create baskets. Generally,institutional investors create baskets containing stocks that do notaccurately replicate an exchange-traded index (i.e., an “imperfectbasket”). In contrast, a “perfect basket” accurately reflects thefluctuations of an exchange-traded index. While imperfect baskets havecertain inherent benefits, they present problems when a risk managerattempts to utilize them to hedge a risk.

Where there is no tradable index that adequately mirrors the particularbasket that an investor holds, the investor can devise a hedging vehicleby purchasing an over-the-counter “OTC” put option from an investmentbank whose underlying asset matches the portfolio in question. Indesigning this OTC product the investor may also select a wide array offeatures using exotic options (i.e., average rate, knock-in, knock-out,compound and lookback options, etc.) that structure the risk/rewardratio in a variety of different forms.

Referring to FIG. 9, shown is an example of a self insured employerusing a basket of financial derivatives based on both a healthcare indexand a healthcare sub-index to manage its risk against healthcare costvolatility in accordance with the present invention. As in previousexamples, an entity initially predicts its expected healthcare costs asdepicted in step 901. In this example a Company's total medical expensesin the previous year were $40 million and costs are expected to rise 10%to 44 million the following year. In addition, the Company estimatesthat 50% of its total costs are related to prescription drug claims.Thus, the company predicts that it will incur $22 million in claimsrelated to prescription drugs and $22 million for all other claims.

After predicting its costs, the Company must determine the appropriatenumber of futures contracts to sell in order to effectively hedgeagainst the calculated risk associated with the prediction of step 901.In this example it is assumed that contemporaneous futures contracts forboth the prescription drug index and the healthcare index are trading at$90.00, reflecting a 10% increase in the NIPA healthcare index and theprescription drug sub-index over the course of the year. Again, usingthis data as a starting point, the Company decides how much riskexposure it wishes to hedge against forming a hedge ratio in any mannerthat is well known in the art to calculate the number of contracts tosell.

After determining the number of contracts to sell, the Company wouldsell the requisite number of contracts 905. In this example of theembodiment of the present invention, we assume that the Companydetermines that it will sell 20 contracts at $90.00 per contract foreach index for a total of 40 contracts. It is also assumed that thevalue of the healthcare index on the date of sale is $4000 and theprescription drug index is $800. The Company can either construct customfutures contracts in the manner previously described or use astandardized futures contract, and we assume the quantity of eachstandardized contract is 10,000 units per contract.

The Company may then offer either set of futures contracts for saleprivately, over the counter, or publicly on an exchange. In thepresently described embodiment, the contracts are offered on anexchange, but in alternative embodiments, the contracts could bestandardized and offered on an exchange or the Company could constructthe contracts in any manner that it chooses and offer them for sale inany manner.

After offering the contacts for sale, the Company can allow thecontracts to settle as shown in step 907. Alternatively, it can managethe futures contracts in any manner known, including repurchasing anyportion of the contracts it has offered on any day at a value determinedby the index price, or sell more contracts at the market price.

On the settlement date of the futures contracts, the Company deliversits contracts. The value of the healthcare index on the settlement dateis used to determine the settlement price. In the currently describedembodiment, it is assumed that on the settlement date the healthcarecost index increased to $4400 and the prescription drug index increasedto $910. The contract values are then determined by the below formula:100−(100*((Index Value on settlement date/index value on offer date)−1))In the present case, the healthcare contract value is $90.00 and theprescription index contract is $86.25.

To determine its total profit or loss, the Company uses the formula:# Units/contract*# of contracts*price difference=Profit (Loss)In the previously described embodiment the Company would profit in theamount $750,000 for the prescription drug contracts and would not profitfrom the sale of healthcare index contracts.

In the presently described embodiment, the healthcare index rose at theexpected threshold of 10%. The actual percentage increase of theprescription drug index can be determined by using the below formula:((Index Value at Settlement/Index Value at Offering)/Index Value atoffering))*100%In the presently described embodiment, the prescription drug index rose13.75%. Because the volatility of the prescription drug index was higherthan expected and the prescription drug index is correlated to drug costincreases, the Company's yearly predictions related to them were toolow. Similarly, because the healthcare index was exactly what waspredicted, the Company's healthcare related predictions were spot on.

It is assumed in this case that the Company incurred medical expenses of$46 million, of which the entire increase is attributable to theincrease in prescription drug claims incurred (i.e., the incurredprescription drug claims were actually $24 million and the otherincurred claims were $22 million). To properly hedge against itserroneous predictions, the Company applies the proceeds 909 from thesale of the contracts (e.g. $750,000) to the increased cost ofhealthcare. In the presently described embodiment, the Company has a netloss of $1,250,000, the difference between the increase in predictedcosts and the monies earned on the futures contracts. While the Companyincurred a net loss of $1,250,000, without utilizing a basket ofderivatives, the Company would have incurred a net loss of $2,000,000.

Table 6 below illustrates the benefits to the Company of managing riskutilizing a basket of financial derivatives based on the indices inaccordance with the present invention: TABLE 6 Basket of Derivatives V.No Basket No Basket of Basket of Derivatives Derivatives PrescriptionHealthcare Prescription Healthcare Company Index Index Index IndexNumber of Contracts 0 40 20 20 Purchased Price of Contract 90 90 90 90Initial Value of 4000 4000 Healthcare Index Expected Value of 4400 4400Healthcare Index at Settlement Actual Value of 4400 4400 HealthcareIndex at Settlement Actual Value of 0 0 Healthcare Proceeds atSettlement Initial Value of 800 800 Prescription Drug Index ExpectedValue of 880 880 Prescription Drug Index at Settlement Actual Value of910 910 Prescription Drug Index at Settlement Actual Value of 0 $750,000Prescription Drug Proceeds at Settlement Total Increase in $2,000,000$2,000,000 Expenses Total Hedge 0 $750,000 Proceeds Total Profit/Loss($2,000,000)      ($1,250,000)     

As the table illustrates, the company's insurance costs were the leastvariable using a basket of futures derivative in accordance with thepresent invention. If the company chose not to hedge its risk, its totalvariability is ±$2 million. In addition, because all of the volatilitywas due to an increase in prescription drug claims, managing risk with ahealthcare derivative is ineffective.

However, by utilizing futures contracts based on a basket ofderivatives, the company's total variability is limited to −$1,250,000which allows the company to better predict its future earnings.

1. A method of providing a healthcare related derivative instrumentcomprising the steps of: calculating a healthcare index value based onat least one healthcare related data source; pricing a derivativeinstrument relative to said healthcare index value; and providing saidderivative instrument.
 2. The method of claim 1 wherein said healthcarerelated index further comprises an index value which correlates to theUnited States healthcare trend.
 3. The method of claim 1 wherein saidhealthcare related data source is National Income and Product Accountsdata.
 4. The method of claim 2 wherein said National Income and ProductAccounts data further comprises data selected from the group consistingof prescription drugs data, workmen's compensation data, and medicalcare and hospitalization data.
 5. The method of claim 1 wherein saiddata source comprises at least one data source selected from the groupconsisting of: the medical consumer price index, the producer priceindex, national health accounts, medical expenditure panel survey,medicare economic and price index, Kaiser/HRET annual employer healthbenefits survey, AHA annual survey, Mercer national survey of employersponsored health plans, Ingenix, Milliman health cost index, andMedstat.
 6. The method of claim 1 wherein said derivative instrumentcomprises at least one selected from the group consisting of a futurescontract, an option, and a futures option.
 7. A method according toclaim 1 wherein said derivative instrument comprises a settlement price.8. The method of claim 7 wherein said settlement price is determinedperiodically.
 9. The method of claim 8 wherein said period is selectedfrom the group consisting of daily, weekly, monthly, quarterly, andannually.